目的 筛选空间环境诱变的肺炎克雷伯菌突变株及并进行全转录组分析.方法 利用Biolog生化反应板从搭载于神舟八号飞船的肺炎克雷伯菌中筛选突变株,然后采用高通量测序技术对突变株全转录组测序,原始测序数据经处理后进行基因表达注释和差异表达基因的基因本体功能及京都基因与基因组信号通路注释分析.结果 空间搭载的肺炎克雷伯菌突变株在糖类代谢上出现差异,且该菌株有232个基因表达上调,1 879个基因下调,其主要同细菌的膜蛋白、转运相关功能、糖类的运输相关.结论 获得一株空间环境诱导的肺炎克雷伯菌突变株且该菌株全转录组测序和注释清晰,为后续的功能研究奠定了基础.

The environment in space could affect microorganisms by changing a variety of features, including proliferation rate, cell physiology, cell metabolism, biofilm production, virulence, and drug resistance. However, the relevant mechanisms remain unclear. To explore the effect of a space environment on Bacillus cereus, a strain of B. cereus was sent to space for 398h by ShenZhou VIII from November 1, 2011 to November 17, 2011. A ground simulation with similar temperature conditions was simultaneously performed as a control. After the flight, the flight and control strains were further analyzed using phenotypic, genomic, transcriptomic and proteomic techniques to explore the divergence of B. cereus in a space environment. The flight strains exhibited a significantly slower growth rate, a significantly higher amikacin resistance level, and changes in metabolism relative to the ground control strain. After the space flight, three polymorphic loci were found in the flight strains LCT-BC25 and LCT-BC235. A combined transcriptome and proteome analysis was performed, and this analysis revealed that the flight strains had changes in genes/proteins relevant to metabolism. In addition, certain genes/proteins that are relevant to structural function, gene expression modification and translation, and virulence were also altered. Our study represents the first documented analysis of the phenotypic, genomic, transcriptomic, and proteomic changes that occur in B. cereus during space flight, and our results could be beneficial to the field of space microbiology.

Klebsiella pneumoniae is a gram-negative, nonmotile, encapsulated, lactose-fermenting, facultative anaerobic, rod-shaped bacterium found in the normal flora of the mouth, skin, and intestines. Here we present the fine-draft genome sequence of K. pneumoniae strain LCT-KP214, which originated from K. pneumoniae strain CGMCC 1.1736.

Legionella (Fluoribacter) dumoffii is one of the agents causing Legionnaires' disease. Here, we used Illumina second-generation sequencing technology to decipher for the first time the whole-genome sequences of two strains of this species, TEX-KL and NY-23. The assembly results for both strains consist of one chromosome and two plasmids.

An outbreak caused by Shiga-toxin–producing Escherichia coli O104:H4 occurred in Germany in May and June of 2011, with more than 3000 persons infected. Here, we report a cluster of cases associated with a single family and describe an open-source genomic analysis of an isolate from one member of the family. This analysis involved the use of rapid, bench-top DNA sequencing technology, open-source data release, and prompt crowd-sourced analyses. In less than a week, these studies revealed that the outbreak strain belonged to an enteroaggregative E. coli lineage that had acquired genes for Shiga toxin 2 and for antibiotic resistance.

In the genomic era, new techniques and criteria are proposed to improve the traditionally phenotypic and biochemical test–based approaches for prokaryotic species definition. Among them, average nucleotide identity (ANI) mirrors DNA-DNA hybridization and is widely used by the microbial research community. However, our test shows that ANI possibly defines distinct taxa as the same species when they shared highly homologous sequences in a very short genomic region. In this study, we propose an improved algorithm named total nucleotide identity (TNI) for use in bacterial taxonomy; this algorithm provided higher accuracy for species classification than ANI. Furthermore, we developed a species identification system for prokaryotes (SISP) based on pairwise TNI of 3,073 genomes acquired from GenBank. For a submitted query genome, SISP can quickly find its most closely related genome from the established database based on the TNI calculation and infer the possible species of the query genome. Given a criterion of TNI > 70%, SISP has an accuracy that was above 90% for 3,596 prokaryotic genomes. SISP is open source and is available at https://github.com/chjp/SISProkaryotes.